Transcranial Pulse Stimulation (TPS®) as a method for treating the central nervous system of patients with Alzheimer’s disease
Bibliographic record
Abstract
Introduction Dementia - one of the most common diseases in old age - is often only diagnosed at a late stage. Therefore patients with dementia have often a 1.4 to 3.6 times greater risk of treatment as an inpatient. Consequently it is highly relevant within the caring system to identify and treat the onset of dementia at the earliest possible opportunity. Objectives Part of a new treatment center, a psychiatric clinic in the Hanover area (Wahrendorff ) has concentrated on treating patients with a mild or moderate form of Alzheimer’s disease as early as possible on an outpatient basis. The method of transcranial pulse stimulation (TPS®) is used. Acoustic pulses generated outside the body are introduced specifically into the brain regions requiring treatment. The aim being the release of growth factors and an improvement in cerebral blood flow, as a means to maintaining and promoting cognitive performance for as long as possible. The poster contribution shows reports from clinicians, patients and relatives, using TPS®. The development of cognitive performance in the course of treatment is also considered. Methods The data collection for the quantitative study design will take place at the clinic in the period from 06/2021 to 10/2022 (N planned = 60). Cognitive performance is recorded using the Montreal Cognitive Assessment (MoCA test) and the experience reports via interview. Results Results of repeated measurement and analysis of the variance in terms of cognitive performance (MoCA test, baseline and follow-up measures) are presented. Field reports are considered and the suitability of TPS® as a method for treating the symptoms of dementia in Alzheimer’s disease is discussed in the form of a best-practice example. Conclusions Field reports are considered and the suitability of TPS® as a method for treating the symptoms of dementia in Alzheimer’s disease is discussed in the form of a best-practice example. Disclosure of Interest None Declared
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".